
#import dependencies
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sb
import helpers
import matplotlib.dates as mdates
import plotly.express as px
import plotly.graph_objects as go
import re
import warnings
warnings.filterwarnings('ignore')
sb.set_style("darkgrid")
%matplotlib inline


# load data
df = pd.read_csv("cleaned_data/reddit_cleaned_2020.csv")
df_merged = pd.read_csv("cleaned_data/reddit_merged_2020.csv")


# convert to datetime
df.created_at = pd.to_datetime(df.created_at)
df_merged.created_at = pd.to_datetime(df_merged.created_at)
df_merged.user_created_at = pd.to_datetime(df_merged.user_created_at)


print(df.shape)
df.head(2);

(128408, 17)


print(df_merged.shape)
df_merged.head(2);

(128408, 24)


# Filter on banned accounts
df_banned = df_merged[df_merged['is_banned']]
print(df_banned.shape)
df_banned.head(2);

(10235, 24)


# Filter on unverified accounts
df_unverified = df_merged[~df_merged['has_verified_email']]
print(df_unverified.shape)
df_unverified.head(2);

(17048, 24)


# Filter on Accounts created in the last 4 years
df_4 = df_merged[df_merged['user_created_at'].dt.year.isin([2018, 2019, 2020])]
print(df_4.shape)
df_4.head(2);

(46951, 24)


# Filter on Accounts created in 2018
df_18 = df_merged[df_merged['user_created_at'].dt.year == 2018]
print(df_18.shape)
df_18.head(2);

(13125, 24)


# Filter on Accounts created in 2019
df_19 = df_merged[df_merged['user_created_at'].dt.year == 2019]
print(df_19.shape)
df_19.head(2);

(20104, 24)


# Filter on Accounts created in 2020
df_20 = df_merged[df_merged['user_created_at'].dt.year == 2020]
print(df_20.shape)
df_20.head(2);

(13722, 24)


peak_day = '2020-02-04'


# Filter on Peak Day 
df_peak = df_merged[df_merged['created_at'].dt.date.astype('str') == peak_day]
df_peak_submissions = df_peak.query("submission_comment == 'submission'")


# Filter on Peak Day For Unverified accounts
df_unverified_peak = df_unverified[df_unverified['created_at'].dt.date.astype('str') == peak_day]
df_unverified_peak_submissions = df_unverified_peak.query("submission_comment == 'submission'")


# Filter on Submissions
df_submissions = df_merged.query("submission_comment == 'submission'")
df_unverified_submissions = df_unverified.query("submission_comment == 'submission'")


colors = px.colors.qualitative.T10

fig = px.pie(df_merged.banned_unverified.value_counts().to_frame().reset_index(),
             values='banned_unverified', names='index', color_discrete_sequence = colors,
             title = 'Contributions of banned / unverified /others in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_merged, x='banned_unverified', color="banned_unverified", 
                    color_discrete_sequence = colors, 
                   title = 'Contributions of banned / unverified /others in 2020')
fig.show()


fig = px.pie(df_peak.banned_unverified.value_counts().to_frame().reset_index(),
             values='banned_unverified', names='index', color_discrete_sequence = colors,
             title = 'Contributions of banned / unverified /others on the peak day (2020-02-04)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


15.4+6.77

22.17


fig = px.histogram(df_peak, 
                   x='banned_unverified', color="banned_unverified", 
                   color_discrete_sequence = colors, 
                   category_orders = dict(creation_year=['2018', '2019', '2020',  'banned', 'others']),
                   title = 'Contributions of banned / unverified /others on the peak day (2020-02-04)')
fig.show()


fig = px.pie(df_submissions.banned_unverified.value_counts().to_frame().reset_index(),
             values='banned_unverified', names='index', color_discrete_sequence = colors,
             title = 'Submissions of banned / unverified /others in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_submissions, x='banned_unverified', color="banned_unverified", 
                   color_discrete_sequence = colors, 
                   title = 'Submissions of banned / unverified /others in 2020')
fig.show()


fig = px.pie(df_peak_submissions.banned_unverified.value_counts().to_frame().reset_index(),
             values='banned_unverified', names='index', color_discrete_sequence = colors,
             title = 'Submissions of banned / unverified /others on the peak day (2020-02-04)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_peak_submissions, x='banned_unverified', color="banned_unverified", 
                    color_discrete_sequence = colors, 
                   title = 'Submissions of banned / unverified /others on the peak day (2020-02-04)')
fig.show()


df_banned.score.describe()

count    10226.000000
mean        29.981713
std        548.530475
min       -216.000000
25%          1.000000
50%          2.000000
75%          6.000000
max      36851.000000
Name: score, dtype: float64


# Filter on largest scores

df_scores_high = df_banned.sort_values('score', ascending=False).head(10)

fig = px.bar(df_scores_high,
             x='user_name', 
             y=df_scores_high.score, text = df_scores_high.score, title='Banned accounts highest contribution scores')

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_high.user_name,
    )
)

clrs = ['red' if (y > 5000) else '#5296dd' for y in df_scores_high.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')

# , marker_line_color='#5296dd'

fig.show()


df_crack = df_banned[df_banned.user_name == 'cracksniffer666'].sort_values('created_at')
df_crack.head()


df_crack.submission_comment.value_counts()

comment       98
submission     1
Name: submission_comment, dtype: int64


df_crack.text.value_counts()

I don't believe in canceling people. She should go to kangaroo court.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 1
It's sad that healthy, lovely, young women and men are getting shown this shit. It truly upsets me, and I'm scared to have children at this point. If I have a son, I have to worry, if I have a daughter, I have to worry twice as much. Just doesn't seem worth it, wish we could hit the 90s one more time, lol                                                                                                                                                                                                                                                                                                                    1
You're a misogynist for thinking she should be treated as a man would. What world do you live in? EQUALITY.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           1
What I want to do, is blame him for not walking away, but ladies and men both know, when you got that TRUE LOVE for someone, (or so you think) it's like a fucking drug, and you aren't rational. That's why I give some people a little leeway when it comes to relationships, because love is the strongest drug in the fucking world, and people play with it like it's candy cigarettes                                                                                                                                                                                                                                           1
Doubts. My Answer is no. Probably get another movie deal knowing Hollywood.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           1
                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     ..
That's pathetic                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       1
Feel free to come on my podcast and air it out                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        1
Maybe I'll meme the Elon musk thing next, since women can do no wrong on reddit. I HAVE TO ASK.... do dudes that blindly defend women on here, think they're gonna get laid, by a random, anynomous person? I've never understood that. Is it cognitive dissonance? "well, I defended m'lady, now I can sleep soundly tonight..." like I literally don't know what their main objective is.. I respect my mother, my sister, and the couple chicks I hangout wit/hook up with, and I can't see blindly defending someone if they're wrong.. My mind just can't do it. I'm glad these Neckbeards aren't attourneys/judges... Fuck..    1
Username checks out. No. No we can't.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 1
Thank you for actually providing a decent argument and showing me how I'm wrong on certain points. That's what I came here for, 7 years ago, and it's rare now. Cheers. I'll try. Everyone has their own story. I'll try to better my ending.                                                                                                                                                                                                                                                                                                                                                                                         1
Name: text, Length: 99, dtype: int64


df_crack_contributions = df_crack.groupby(df_crack.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(df_crack_contributions,
             x='created_at', 
             y='n_contributions', title='"cracksniffer666" contributions in 2020')

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = df_crack_contributions.created_at,
    )
)

fig.update_traces(marker_color='red',
                  marker_line_width=1
                , opacity=1)
fig.show()


# Filter on minimum scores

df_scores_low = df_banned.sort_values('score').head(20)

fig = px.bar(df_scores_low,
             x='user_name', 
             y=df_scores_low.score, 
             text = df_scores_low.score)

fig.update_layout(title_text='Banned accounts minimum contribution scores', title_x=0.5, title_y=0.2)

fig.update_layout(
    xaxis = dict(
        side='top',
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_low.user_name,
    )
)

clrs = ['red' if (y < -120) else '#5296dd' for y in df_scores_low.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


df_pp = df_banned[df_banned.user_name == 'WouldYouKindley88']
df_pp.sort_values('created_at', inplace=True);


df_pp


df_pp.submission_comment.value_counts()

comment    37
Name: submission_comment, dtype: int64


# df_amazing.permalink[15599]


df_hec = df_banned[df_banned.user_name == 'hecubus452']
df_hec.sort_values('created_at', inplace=True)
df_hec


fig = px.pie(df_merged.is_banned.value_counts(),
             values='is_banned', names=['others', 'banned'], color_discrete_sequence = colors,
             title = 'Contributions of Banned accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


print('The percentage % of 2020 contributions made by Banned accounts:')
banned_contr_prop = df_banned.shape[0] * 100 /df_merged.shape[0]
banned_contr_prop

The percentage % of 2020 contributions made by Banned accounts:

7.9706871845990905


px.bar(data_frame=df_merged['is_banned'].value_counts(),
       x=['others', 'banned'], y="is_banned").update_layout(title='Contributions of Banned accounts in 2020',
                   xaxis_title='',
                   yaxis_title='n_contributions').update_traces(marker_color='#5296dd')


print('Total banned accounts contributions in 2020:')
df_banned.shape[0]

Total banned accounts contributions in 2020:

10235


print('Total banned accounts comments in 2020:')
df_banned.query(" submission_comment == 'comment' ").shape[0]

Total banned accounts comments in 2020:

9060


df_banned.query(" submission_comment == 'comment' ").text.value_counts().head(5)

Lol                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     9
No                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      9
Doug Stanhope was right.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                7
In the audio she continually shames him for attempting to remove himself from the situation when it gets violent. He acknowledges the unhealthiness of the situation while she attempts to minimalist and normalize it and calls him a baby and issues gendered insults at him for his habit of leaving the room when she gets violent.\n\nThe amount of uninformed “well but maybe he also...” that’s going on in these comments, especially from female commenters, is absurd, and it makes the complaints of MRAs feel like maybe there’s a nugget of truth in there about a society that minimizes abuse of men and rationalizes abuse by women.    6
Amber Turd                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              5
Name: text, dtype: int64


fig = px.pie(df_submissions.is_banned.value_counts(),
             values='is_banned', names=['others', 'banned'], color_discrete_sequence = colors,
             title = 'Submissions of Banned accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


print('The percentage % of 2020 submissions made by Banned accounts:')
banned_sub_prop = df_banned.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

banned_sub_prop

The percentage % of 2020 submissions made by Banned accounts:

14.905492832677915


px.bar(data_frame=df_submissions['is_banned'].value_counts(),
       x=['others', 'banned'], y="is_banned").update_layout(title='Submissions of Banned accounts in 2020',
                   xaxis_title='',
                   yaxis_title='n_submissions').update_traces(marker_color='#5296dd')


print('Total banned accounts submissions in 2020:')
df_banned.query(" submission_comment == 'submission' ").shape[0]

Total banned accounts submissions in 2020:

1175


df_banned.query(" submission_comment == 'submission' ").text.value_counts().head(5)

Amber Heard                                                                                                                                                                                                                                                                                              84
I'm glad that abused men are finally being taken seriously after the Johnny Depp x Amber Heard fiasco.                                                                                                                                                                                                   25
Amber Heard has disgraced and discredited actual survivors of domestic abuse. Gender means nothing when it comes to abuse. Men can be and are victims too. She should not be in any position of leadership and should be removed from all of L’Oréal’s campaigns. Sign the petition to get rid of her    13
Johnny Depp & Amber Heard Abuse Claims: Australia's Bloody Aftermath! NEW UNCENSORED AUDIO!!                                                                                                                                                                                                             11
Sign the Petition: Remove Amber Heard from Aquaman 2                                                                                                                                                                                                                                                     11
Name: text, dtype: int64


txt = 'Amber Heard'
df_banned[df_banned['text'] == txt][['user_name', 'subreddit', 'created_at']]

# Nothe that we don't have data on banned users except for their names


df_banned[df_banned['text'] == txt][['user_name', 'subreddit', 'created_at']].groupby('user_name').count().sort_values('subreddit', ascending=False).head(11)


df_banned[df_banned['user_name'] == 'armpit-lover'].subreddit.value_counts()

r/CelebrityArmpits    13
r/celebnsfw            7
r/goddesses            1
r/Celebs               1
r/Celebhub             1
r/JerkOffToCelebs      1
Name: subreddit, dtype: int64


txt = """I'm glad that abused men are finally being taken seriously after the Johnny Depp x Amber Heard fiasco."""
rod = df_banned[df_banned['text'] == txt][['user_name', 'subreddit', 'created_at']]
rod
# Nothe that we don't have data on banned users except for their names


rod.user_name.value_counts()

rodrigohernandez4477    25
Name: user_name, dtype: int64


rod.subreddit.value_counts()

r/Toxic_Femininity         1
r/padresconderecho         1
r/Egalitarianism           1
r/JordanPeterson           1
r/ProMaleCollective        1
r/antifeminists            1
r/LeftistsForMen           1
r/AbuseInterrupted         1
r/MenToo                   1
r/MRActivism               1
r/socialjustice            1
r/masculinismo             1
r/PussyPass                1
r/Feministpassdenied       1
r/HimToo                   1
r/Equality                 1
r/LadyMRAs                 1
r/PadresConDerechos        1
r/MensRightsMeta           1
r/activism                 1
r/TrueUnpopularOpinion     1
r/TalesofPrivilege         1
r/AntiPinkPill             1
r/AgainstMisandry          1
r/SocialJusticeWarriors    1
Name: subreddit, dtype: int64


rod.created_at.dt.date.value_counts()

2020-12-05    13
2020-11-28    12
Name: created_at, dtype: int64


rod[rod.created_at.dt.date.astype(str) == '2020-12-05'].created_at.max() - rod[rod.created_at.dt.date.astype(str) == '2020-12-05'].created_at.min()

Timedelta('0 days 00:20:30')


rod[rod.created_at.dt.date.astype(str) == '2020-11-28'].created_at.max() - rod[rod.created_at.dt.date.astype(str) == '2020-11-28'].created_at.min()

Timedelta('0 days 00:13:21')


# group by date an count
banned_contributions = df_banned.groupby(df_banned.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(banned_contributions,
             x='created_at', y='n_contributions')

fig.update_layout(
            title={
        'text': "The number of banned users contributions created on each date",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=.5, opacity=1, textposition='auto').update_layout()
fig.show()


banned_contributions.sort_values('n_contributions', ascending=False).head(10)


# sort by n_contributions, take the top 3, then sort them by date 
banned_contributions.sort_values('n_contributions', ascending=False, inplace=True)
banned_trendy = banned_contributions.head(5)
banned_trendy.sort_values('created_at', inplace=True)

fig = px.bar(banned_trendy,
             x='created_at', y='n_contributions')

fig.update_layout(
            title={
        'text': "The number of banned users contributions on peak dates",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = banned_trendy.created_at,
    )
)

clrs = ['red' if (y > 60) else '#5296dd' for y in banned_trendy['n_contributions']] 

fig.update_traces(marker_color=clrs,
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


link_high_users = df_unverified.sort_values('link_karma', ascending=False).user_name.unique()[:10]

df_link_high = df_unverified.sort_values('link_karma', ascending=False)\
[df_unverified.sort_values('link_karma', ascending=False)\
 .user_name.isin(link_high_users)]


# Filter on largest link karma

#df_link_high = df_unverified.sort_values('link_karma', ascending=False).head(10)

fig = px.bar(df_link_high,
             x='user_name', 
             y=df_link_high.link_karma, text = df_link_high.link_karma, title='Unverified accounts with highest link karma')

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_link_high.user_name,
    )
)

clrs = ['red' if (y > 2000000) else '#5296dd' for y in df_link_high.link_karma]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')

# , marker_line_color='#5296dd'

fig.show()


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_unverified[df_unverified.user_name == 'agree-with-you'].head(1))


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_unverified[df_unverified.user_name == 'WikiTextBot'].head(1))


link_high_users = df_unverified.sort_values('comment_karma', ascending=False).user_name.unique()[:10]

df_comment_high = df_unverified.sort_values('comment_karma', ascending=False)\
[df_unverified.sort_values('link_karma', ascending=False)\
 .user_name.isin(link_high_users)]


# Filter on largest comment karma

fig = px.bar(df_comment_high,
             x='user_name', 
             y=df_comment_high.comment_karma, text = df_comment_high.comment_karma, title='Unverified accounts with highest comment karma')

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_comment_high.user_name,
    )
)

clrs = ['red' if (y > 2000000) else '#5296dd' for y in df_comment_high.comment_karma]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')

# , marker_line_color='#5296dd'

fig.show()


df_unverified[df_unverified.user_name == 'agree-with-you'].created_at

27968   2020-02-02 13:35:15
27969   2020-02-02 17:48:25
27970   2020-02-02 18:38:52
27971   2020-02-03 13:10:12
27972   2020-02-04 20:17:08
27973   2020-02-05 15:41:16
27974   2020-02-09 10:01:35
27975   2020-02-13 12:08:43
27976   2020-07-03 06:54:37
27977   2020-08-13 09:31:14
Name: created_at, dtype: datetime64[ns]


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_unverified[df_unverified.user_name == 'agree-with-you'].head(1))


# Filter on minimum link karma

df_link_low = df_unverified.sort_values('link_karma').head(20)

fig = px.bar(df_link_low,
             x='user_name', 
             y=df_link_low.link_karma, 
             text = df_link_low.link_karma)

fig.update_layout(title_text='Unverified accounts with minimum link karma', title_x=0.5)

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_link_low.user_name,
    )
)

clrs = ['red' if (y < -60) else '#5296dd' for y in df_link_low.link_karma]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


# Filter on minimum comment karma

df_comment_low = df_unverified.sort_values('comment_karma').head(20)

fig = px.bar(df_comment_low,
             x='user_name', 
             y=df_comment_low.comment_karma, 
             text = df_comment_low.comment_karma)

fig.update_layout(title_text='Unverified accounts with minimum comment karma', title_x=0.5, title_y=0.1)

fig.update_layout(
    xaxis = dict(
        side='top',
        title='user name',
        tickmode = 'array',
        tickvals = df_comment_low.user_name,
    )
)

clrs = ['red' if (y < -30) else '#5296dd' for y in df_comment_low.comment_karma]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


df_unverified[df_unverified.user_name == 'rMemesMods']

# Defending AH


df_unverified[df_unverified.user_name == 'jesseboop']


df_unverified[df_unverified.user_name == 'dickless-rodney']

# Defending AH


df_unverified[df_unverified.user_name == 'Coagulate']


df_unverified.score.describe()

count    17043.000000
mean        23.014258
std        473.097606
min       -113.000000
25%          1.000000
50%          2.000000
75%          6.000000
max      38903.000000
Name: score, dtype: float64


# Filter on largest scores

df_scores_high = df_unverified.sort_values('score', ascending=False).head(10)

fig = px.bar(df_scores_high,
             x='user_name', 
             y=df_scores_high.score, text = df_scores_high.score, title='Unverified accounts with highest contribution scores in 2020')

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_high.user_name,
    )
)

clrs = ['red' if (y > 2500) else '#5296dd' for y in df_scores_high.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_unverified[df_unverified.user_name == 'Lucaswebb'].head(1))

# Negative Submission


with pd.option_context('display.max_colwidth', None):
  display(df_unverified[df_unverified.user_name == 'Lucaswebb'].head(1))

# Negative Submissions and Comments


# Filter on minimum scores

df_scores_low = df_unverified.sort_values('score').head(20)

fig = px.bar(df_scores_low,
             x='user_name', 
             y=df_scores_low.score, 
             text = df_scores_low.score)

fig.update_layout(title_text='Unverified accounts with minimum contribution scores in 2020', title_x=0.5, title_y=0.2)

fig.update_layout(
    xaxis = dict(
        side='top',
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_low.user_name,
    )
)

clrs = ['red' if (y < -45) else '#5296dd' for y in df_scores_low.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


df_unverified[df_unverified.user_name == 'wetnewt']


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_unverified[df_unverified.user_name == 'goldenmom1'].head(1))


with pd.option_context('display.max_colwidth', None):
  display(df_unverified[df_unverified.user_name == 'karma-armageddon'].head(2))

# Defending AH


fig = px.pie(df_merged.has_verified_email.value_counts(),
             values='has_verified_email', names=['verified', 'unverified'], color_discrete_sequence = colors,
             title = 'Contributions of Unverified accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


print('The percentage % of 2020 contributions made by Unverified accounts:')
unverified_contr_prop = df_unverified.shape[0] * 100 /df_merged.shape[0]
unverified_contr_prop

The percentage % of 2020 contributions made by Unverified accounts:

13.276431374992212


px.bar(data_frame=df_merged['has_verified_email'].value_counts().to_frame().reset_index(),
       x=['verified', 'unverified'], y="has_verified_email").update_layout(title='Contributions of Unverified accounts in 2020',
                   xaxis_title='',
                   yaxis_title='n_contributions').update_traces(marker_color='#5296dd')


print('Total unverified accounts contributions in 2020:')
df_unverified.shape[0]

Total unverified accounts contributions in 2020:

17048


fig = px.pie(df_peak.has_verified_email.value_counts(),
             values='has_verified_email', names=['verified', 'unverified'], color_discrete_sequence = colors,
             title = 'Contributions of Unverified accounts on peak day (04-02-2020)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


print('Total banned accounts comments in 2020:')
df_unverified.query(" submission_comment == 'comment' ").shape[0]

Total banned accounts comments in 2020:

16537


df_unverified.query(" submission_comment == 'comment' ").text.value_counts().head(5)

Incel                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  21
Yes                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    15
No                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     12
Thanks for your submission, but it has been removed for the following reason: \n\n* **Disallowed question area:** **Loaded question *or* rant.**  NSQ does not allow questions not asked in good faith, such as rants disguised as questions, asking loaded questions, pushing hidden or overt agendas, attempted pot stirring, [sealioning](https://en.wikipedia.org/wiki/Sea_lioning), etc.\n\n NSQ is not a debate subreddit.  Depending on the subject, you may find your question better suited for r/ChangeMyView, r/ExplainBothSides, r/PoliticalDiscussion, r/rant, or r/TooAfraidToAsk.\n\n**This action was performed by a bot at the explicit direction of a human.  This was not an automated action, but a conscious decision by a sapient lifeform charged with moderating this sub.**\n\n*If you feel this was in error, or need more clarification, please don't hesitate to [message the moderators](http://www.reddit.com/message/compose?to=%2Fr%2FNoStupidQuestions).  Thanks.*    12
Amber Turd                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             11
Name: text, dtype: int64


fig = px.pie(df_submissions.has_verified_email.value_counts(),
             values='has_verified_email', names=['verified', 'unverified'], color_discrete_sequence = colors,
             title = 'Submissions of Unverified accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


print('The percentage % of 2020 submissions made by Unverified accounts:')
unverified_sub_prop = df_unverified.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

unverified_sub_prop

The percentage % of 2020 submissions made by Unverified accounts:

6.4823036914880126


px.bar(data_frame=df_submissions['has_verified_email'].value_counts(),
       x=['verified', 'unverified'], y="has_verified_email")\
       .update_layout(title='Submissions of Unverified accounts in 2020',
                      xaxis_title='',
                      yaxis_title='n_submissions').update_traces(marker_color='#5296dd')


print('Total unverified accounts submissions in 2020:')
df_unverified.query(" submission_comment == 'submission' ").shape[0]

Total unverified accounts submissions in 2020:

511


df_unverified.query(" submission_comment == 'submission' ").text.value_counts().head(5)

Amber Heard                                                                37
Amber heard                                                                 5
Amber Heard Allegedly Faked Bloody Nose, Abused Johnny Depp Emotionally     5
How Amber Heard Ruined Jonny Depp’s Career With Lies                        3
All my homies hate Amber Heard                                              3
Name: text, dtype: int64


txt = 'Amber Heard'
df_unverified[df_unverified['text'] == txt][['user_name', 'user_created_at', 'submission_comment', 'created_at']]

# Note that we don't have data on banned users except for their names.


temp = df_unverified[df_unverified['text'] == txt][['user_name', 'user_created_at', 'submission_comment', 'created_at']]


temp[temp.user_name.isin(temp.user_name.value_counts().head(6).index.values)]


temp[temp.user_name.isin(temp.user_name.value_counts().head(6).index.values)][temp.user_name == 'Boiledboxers1']


df_unverified.columns

Index(['child_id', 'permalink', 'text', 'parent_id', 'subreddit', 'created_at',
       'sentiment_blob', 'sentiment_nltk', 'score', 'top_level',
       'submission_comment', 'submission_text', 'user_name',
       'has_verified_email', 'is_mod', 'is_gold', 'is_banned', 'comment_karma',
       'link_karma', 'user_created_at', 'banned_unverified', 'creation_year',
       'diff', 'days_after_creation'],
      dtype='object')


df_unverified[df_unverified['user_name'] == 'Boiledboxers1'].head(1)[[ 'user_name',
       'has_verified_email', 'is_mod', 'is_gold', 'is_banned', 'comment_karma',
       'link_karma', 'user_created_at', 'banned_unverified', 'creation_year',
        'days_after_creation']]


temp[temp.user_name.isin(temp.user_name.value_counts().head(6).index.values)][temp.user_name == 'baronzemo168']


df_unverified[df_unverified['user_name'] == 'baronzemo168'].head(1)[[ 'user_name',
       'has_verified_email', 'is_mod', 'is_gold', 'is_banned', 'comment_karma',
       'link_karma', 'user_created_at', 'banned_unverified', 'creation_year',
        'days_after_creation']]


fig = px.pie(df_unverified.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Contributions of Unverified accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_unverified, x='creation_year', color="creation_year", 
                    color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Contributions of Unverified accounts in 2020')
fig.show()


fig = px.pie(df_unverified_peak.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Contributions of unverified accounts on the peak day (2020-02-04)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_unverified_peak, x='creation_year', color="creation_year", 
                    color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Contributions of unverified accounts on the peak day (2020-02-04)')
fig.show()


fig = px.pie(df_unverified_submissions.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Submissions of Unverified accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_unverified_submissions, x='creation_year', color="creation_year", 
                   color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Submissions of Unverified accounts in 2020')
fig.show()


df_unverified_peak_submissions


# group by date an count
unverified_contributions = df_unverified.groupby(df_unverified.created_at.dt.date).size().reset_index(name='n_contributions')

fig = px.bar(unverified_contributions,
             x='created_at', y='n_contributions')

fig.update_layout(
            title={
        'text': "The number of contributions by users with unverified mails",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1, opacity=1, textposition='auto').update_layout()
fig.show()


# sort by n_contributions, take the top 3, then sort them by date 
unverified_contributions.sort_values('n_contributions', ascending=False, inplace=True)
unverified_trendy = unverified_contributions.head(5)
unverified_trendy.sort_values('created_at', inplace=True)

fig = px.bar(unverified_trendy,
             x='created_at', y='n_contributions')

fig.update_layout(
            title={
        'text': "The number of unverified users contributions on peak dates",
        'x':0.5,
        'xanchor': 'center',
        'yanchor': 'top'
        })

fig.update_layout(
    xaxis = dict(
        title='Contribution Date',
        tickmode = 'array',
        tickvals = unverified_trendy.created_at,
    )
)

fig.update_traces(marker_color='#5296dd',
                  marker_line_width=1.5, opacity=1, textposition='auto').update_layout()
fig.show()


fig = px.pie(df_merged.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Contributions of newly created accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_merged, x='creation_year', color="creation_year", 
                    color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Contributions of newly created accounts in 2020')
fig.show()


fig = px.pie(df_peak.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Contributions of newly created accounts on the peak day (2020-02-04)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_peak, 
                   x='creation_year', color="creation_year", 
                   color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Contributions of newly created accounts on the peak day (2020-02-04)')
fig.show()


fig = px.pie(df_submissions.creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Submissions of newly created accounts in 2020')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


fig = px.histogram(df_submissions, x='creation_year', color="creation_year", 
                  color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Submissions of newly created accounts in 2020')
fig.show()


fig = px.pie(df_peak.query("submission_comment == 'submission'").creation_year.value_counts().to_frame().reset_index(),
             values='creation_year', names='index', color_discrete_sequence = colors,
             title = 'Submissions of newly created accounts on the peak day (2020-02-04)')

fig.update_traces(textposition='inside', textinfo='percent+label')

fig.show()


df_peak.shape[0]

9630


df_peak.query("submission_comment == 'submission'").shape[0]

76


9630-76

9554


fig = px.histogram(df_merged[(df_merged['created_at'].dt.date.astype('str') == '2020-02-04') &\
                            (df_merged['submission_comment'] == 'submission')], 
                   x='creation_year', color="creation_year", 
                  color_discrete_sequence = colors,
                   category_orders = dict(creation_year=['2018', '2019', '2020', '2020', 'banned', 'others']),
                   title = 'Submissions of newly created accounts on the peak day (2020-02-04)')
fig.show()


print('Total contributions in 2020 made by newly created accounts(last 4 years):')
df_4.shape[0]

Total contributions in 2020 made by newly created accounts(last 4 years):

46951


print('The percentage % of 2020 contributions made by newly created accounts(last 4 years):')
contr_prop_4 = df_4.shape[0] * 100 /df_merged.shape[0]
contr_prop_4

The percentage % of 2020 contributions made by newly created accounts(last 4 years):

36.563921251012395


print('Total comments in 2020 made by newly created accounts(last 4 years):')
df_4.query(" submission_comment == 'comment' ").shape[0]

Total comments in 2020 made by newly created accounts(last 4 years):

44323


# df_4.query(" submission_comment == 'comment' ").text.value_counts().head(5)


print('Total submissions in 2020 made by newly created accounts(last 4 years):')
df_4.query(" submission_comment == 'submission' ").shape[0]

Total submissions in 2020 made by newly created accounts(last 4 years):

2628


print('The percentage % of 2020 submissions made by newly created accounts(last 4 years):')
sub_prop_4 = df_4.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

sub_prop_4

The percentage % of 2020 submissions made by newly created accounts(last 4 years):

33.337561841938346


# df_4.query(" submission_comment == 'submission' ").text.value_counts().head(5)


print('Total contributions in 2020 made by newly created accounts(2018):')
df_18.shape[0]

Total contributions in 2020 made by newly created accounts(2018):

13125


print('The percentage % of 2020 contributions made by newly created accounts(2018):')
contr_prop_18 = df_18.shape[0] * 100 /df_merged.shape[0]
contr_prop_18

The percentage % of 2020 contributions made by newly created accounts(2018):

10.221325774095073


print('Total comments in 2020 made by newly created accounts(2018):')
df_18.query(" submission_comment == 'comment' ").shape[0]

Total comments in 2020 made by newly created accounts(2018):

12541


# df_18.query(" submission_comment == 'comment' ").text.value_counts().head(5)


print('Total submissions in 2020 made by newly created accounts(2018):')
df_18.query(" submission_comment == 'submission' ").shape[0]

Total submissions in 2020 made by newly created accounts(2018):

584


print('The percentage % of 2020 submissions made by newly created accounts(2018):')
sub_prop_18 = df_18.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

sub_prop_18

The percentage % of 2020 submissions made by newly created accounts(2018):

7.4083470759863


# df_18.query(" submission_comment == 'submission' ").text.value_counts().head(5)


print('Total contributions in 2020 made by newly created accounts(2019):')
df_19.shape[0]

Total contributions in 2020 made by newly created accounts(2019):

20104


print('The percentage % of 2020 contributions made by newly created accounts(2019):')
contr_prop_19 = df_19.shape[0] * 100 /df_merged.shape[0]
contr_prop_19

The percentage % of 2020 contributions made by newly created accounts(2019):

15.656345399040559


print('Total comments in 2020 made by newly created accounts(2019):')
df_19.query(" submission_comment == 'comment' ").shape[0]

Total comments in 2020 made by newly created accounts(2019):

19056


# df_19.query(" submission_comment == 'comment' ").text.value_counts().head(5)


print('Total submissions in 2020 made by newly created accounts(2019):')
df_19.query(" submission_comment == 'submission' ").shape[0]

Total submissions in 2020 made by newly created accounts(2019):

1048


print('The percentage % of 2020 submissions made by newly created accounts(2019):')
sub_prop_19 = df_19.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

sub_prop_19

The percentage % of 2020 submissions made by newly created accounts(2019):

13.294431054167195


# df_19.query(" submission_comment == 'submission' ").text.value_counts().head(5)


print('Total contributions in 2020 made by newly created accounts(2020):')
df_20.shape[0]

Total contributions in 2020 made by newly created accounts(2020):

13722


print('The percentage % of 2020 contributions made by newly created accounts(2020):')
contr_prop_20 = df_20.shape[0] * 100 /df_merged.shape[0]
contr_prop_20

The percentage % of 2020 contributions made by newly created accounts(2020):

10.686250077876768


print('Total comments in 2020 made by newly created accounts(2020):')
df_20.query(" submission_comment == 'comment' ").shape[0]

Total comments in 2020 made by newly created accounts(2020):

12726


# df_20.query(" submission_comment == 'comment' ").text.value_counts().head(5)


print('Total submissions in 2020 made by newly created accounts(2020):')
df_20.query(" submission_comment == 'submission' ").shape[0]

Total submissions in 2020 made by newly created accounts(2020):

996


print('The percentage % of 2020 submissions made by newly created accounts(2020):')
sub_prop_20 = df_20.query(" submission_comment == 'submission' ").shape[0] * 100\
/df_merged.query(" submission_comment == 'submission' ").shape[0]

sub_prop_20

The percentage % of 2020 submissions made by newly created accounts(2020):

12.634783711784854


# df_20.query(" submission_comment == 'submission' ").text.value_counts().head(5)


df_merged.score.describe()

count    128358.000000
mean         29.530890
std         704.111076
min        -541.000000
25%           1.000000
50%           2.000000
75%           6.000000
max       98525.000000
Name: score, dtype: float64


# Filter on largest scores

df_scores_high = df_merged.sort_values('score', ascending=False).head(10)

fig = px.bar(df_scores_high,
             x='user_name', 
             y=df_scores_high.score, text = df_scores_high.score, title='Accounts with highest contribution scores in 2020')

fig.update_layout(
    xaxis = dict(
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_high.user_name,
    )
)

clrs = ['red' if (y > 18000) else '#5296dd' for y in df_scores_high.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


df_scores_high.sort_values('score', ascending=False).user_name

36944     KindlyOlPornographer
10955                 -banned-
58190             Ethernetbabe
124266                Hundifer
122808             SpaceMyopia
102770         psycicfrndfrdbr
104123              ImASadRock
12901                 -banned-
55444                Lucaswebb
105600        Jakeinbrawlstars
Name: user_name, dtype: object


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_merged[df_merged.user_name == 'KindlyOlPornographer'])


df_merged[df_merged.user_name == 'KindlyOlPornographer'].shape

(30, 24)


# Filter on minimum scores

df_scores_low = df_merged.sort_values('score').head(20)

fig = px.bar(df_scores_low,
             x='user_name', 
             y=df_scores_low.score, 
             text = df_scores_low.score)

fig.update_layout(title_text='Accounts with minimum contribution scores in 2020', title_x=0.5, title_y=0.2)

fig.update_layout(
    xaxis = dict(
        side='top',
        title='user name',
        tickmode = 'array',
        tickvals = df_scores_low.user_name,
    )
)

clrs = ['red' if (y < -200) else '#5296dd' for y in df_scores_low.score]

fig.update_traces(marker_color=clrs,
                  marker_line_width=2, opacity=1, textposition='auto')


fig.show()


with pd.option_context('display.max_colwidth', None, 'display.max_columns', None):
  display(df_merged[df_merged.user_name == 'Fantastic_Bat'])


for i in df_merged[df_merged.user_name == 'Fantastic_Bat'].text.values:
    print('-', i)

- Nobody's seriously going to praise Rowling right now for anything. She sided with a man accused of abusing a woman, she sided with a transphobe, she still has a problem with LGBTQ representation, PoC representation, cultural appropriation. . . The list goes on and on.
- Except that when women lie about abuse, they're saying it's not happening, rather than that it is happening, and they're doing it out of a desire to protect their abuser, even at the expense of their own lives.

No woman has *ever* lied about having been abused. Some lie about having *not* been abused, but never about having been abused.
- Men *aren't* the victims of domestic violence, though. They're the *perpetrators*.
- We have Heard's testimony, and that video of him getting drunk and being abusive toward her.

More importantly, though, where's the proof that he *wasn't* abusive? That's the more important question.
- She wasn't, though. She sided with an abuser against his victim. She didn't do the right thing, she engaged in victim blaming, much like this thread is doing now.
- Standing behind a wife beater is never the right thing to do.
- Where's the proof he was falsely accused? This video doesn't prove he didn't abuse her, only that she at one point hit him.

When women get violent, it's primarily in self defense, and even then, it's usually after a long period of ongoing abuse.
- I've never been on Tumblr, but I might go there seeing as how it seems that reddit is doing their part to make domestic violence victims afraid to speak out against the men that abuse them.
- I'm not the one protecting perpetrators of domestic violence. You're the one saying that the abuser is the "real victim," when it's a well-known fact that domestic violence is a process by which men dominate women. [Here is a video playlist](https://www.youtube.com/watch?v=5OrAdC6ySiY&list=PLOxLVEKmV5blQ31nQ87LOsnjLXlAeYhBZ).

I would advise watching the whole channel to understand the nature of domestic violence.
- Watch the videos. They'll explain what's going on.
- He's not, though. He beats women. That's not innocence.
- You've clearly not watched them if you honestly believe that.

Domestic violence is intrinsically linked to male privilege. The videos cover this. Watch them, seriously. They'll help you leave behind this toxic masculinity that you're so wrapped up in.
- Amber Heard. He beat Amber Heard. That's why this discussion first started, was because he beat Amber Heard.
- Depp wasn't the victim. Amber Heard was the victim. Depp was the perpetrator. You seriously need to learn more about the Duluth Model.
- No, women lie about abuse all the time. They lie to cover it up, either to protect their abuser, or because they know that if they tell the truth they won't be believed, which puts them in even more danger.
- It just doesn't happen.
- If you look up "the Duluth Model," you'll learn a lot more on the subject of domestic violence, about how it's a system to oppress women, how it ties back to the Patriarchy and male privilege.
- > he fact that women lie about being abused as well. Because that happens very often

And this right here? This is WHY women lie to protect their abusers: Because they know that if they don't, people will say things like this to defend their abusers, they won't be believed, and that their lives will be in that much more danger.

Amber Heard had nothing to gain and everything to lose by coming forward against her abuser, and this thread demonstrates that perfectly. She risked her very life to come forward and expose her abuser. She's a hero, and people are vilifying her, and simultaneously sending the message to other women that "if you come forward against your own abuser, even worse will happen to you."

No, I'm not blind to anything. If anything, it's YOU who are blind to the message this sends to women trapped in abusive relationships everywhere.
- She recorded him abusing her. She flat-out denies punching him. She says she hit him, but women aren't violent for no reason, which means that she was acting in self defense. 

You're pointing to evidence of his guilt and saying it proves him innocent. It doesn't. Her having to defend herself physically against him proves that he was violent toward her.

Seriously, look up the Duluth Model. It explains it far better than I ever could. Violence is a tool of the Patriarchy, not something that women can use against men, and pretending otherwise is just going to perpetuate this myth that women lie about being abused, which is a lie that gets women killed.
- It's the only logical standard when it comes to domestic violence, because women don't lie about domestic violence. Why would they? They gain nothing from it. When women are abused and they come forward, everybody rushes to call them a liar. By coming forward with her story, Amber Heard put her life in danger. Why would she do that over a lie?
- It's funny that something you say isn't "backed up by science" is also the gold standard for dealing with Domestic Violence, being used by pretty much the entire developed world (and in a lot of the US, too).

But I trust the experts here more than I trust someone on the internet claiming to be the one exception to all of objective reality.
- She does not have "a pattern of abuse." Abuse is a system that men use to uphold the patriarchy and maintain male privilege. Women are the victims of this system. Women gain nothing by engaging in the system that is used to oppress them, so why would they engage in it?

Abuse is goal-oriented. Women don't engage in it because they gain nothing from it. They *can't* benefit from it, only men can. The idea that women would engage in it despite men being the beneficiaries of it is absurd.
- And this is why women who are abused are afraid to come forward: They know their abusers will be defended, and they will be labeled as liars. They know it will accomplish nothing but to make their abusers even angrier and to further isolate them.

By refusing to believe a survivor who has come forward with her story, you are helping to perpetuate the violence against women.

Believe women. They won't lie, and their very lives are depending on you believing them.
- And maybe you should be asking what he must've done to drive her to do such things?
- These things arise not from the abuse, but from the patriarchy. The sense of power and control is built in to the framework of patriarchy, the abuse is how it's enforced and maintained.

You're confusing the symptom for the disease.

Women cannot gain these things from abuse, because abuse isn't what grants them. Men can reinforce patriarchy through violence, but women gain nothing by partaking in the very system by which they are oppressed.
- I'm sorry, but he must've done significantly more than that. These things he did weren't isolated incidents causing outbursts, they were part of a sustained pattern of abusive behavior which led, ultimately, to her retaliation in self defense.

Women do not engage in domestic violence. They cannot, as domestic violence is the tool men use to reinforce the patriarchy and assert dominance and male privilege over women.

I'm not assuming anything. This is what the Duluth model tells us about the nature of domestic violence. Nearly every developed country (and even parts of the US) uses either the Duluth model or something nearly identical to or derived from it to deal with domestic violence.

So, is it the entire developed world that is wrong, here, or is it more likely that you are wrong?
- "Delusional" would be to reject what the entire developed world knows to be true in order to protect one abuser from ever facing even a minor inconvenience in his life as a result of his abusing his wife.
- He *almost* lost his job, all because he abused his wife? How horrible! So much worse than suffering years of systematic abuse at the hands of a wife beater until you finally had no choice but to come forward, only to have everyone turn against you because you ever dared to defend yourself against a man who, clearly, everyone seems to think had every right to abuse her for the rest of her life.

Seriously, it's the 21st century. Women are people, and we're on the verge of recognising that legally and maybe affording them some rights and protections under the law. That mindset of yours belongs. . . Well, nowhere, really. Maybe in the US, where they haven't quite caught on to the 20th century, yet.
- If the entire model is faulty, then why is it that the *entire developed world* uses either it, or something nearly identical to it or derived from it to handle domestic violence?

Even most of the US uses the Duluth model, and they're still practically in the stone age.
- You're the one defending a man's right to abuse his wife, here. Accusing *me* of "turning back to 200 years ago" is rather a bit of projection, there. 

You're the one justifying a man doing whatever he wants to his wife because she's his property by refusing to believe a victim of domestic violence when she comes forward about the abuse she suffered at the hands of her husband, accusing her of lying for personal gain (which is a thing that has never happened in the history of, well, ever. No woman has ever lied about domestic violence, and no woman has ever gained anything from accusing her husband of being violent against her. In fact, coming forward destroys a woman's reputation and puts her life at risk. That's a weird thing to do just to try and "get someone," isn't it?)
- If a woman is violent, it's because she was pushed to defend herself against a male oppressor.

Sadly, most women who *do* defend themselves against their batterers often do wind up in jail, because the Patriarchy doesn't like it when women fight back against their own destruction.
- The evidence shows that Depp is guilty. You have Amber Heard's own testimony that she was abused, and you have evidence of her fighting back against her abuser in self defense, and yet you still believe she orchestrated the whole thing to make him look bad, which is the literal opposite of what happened. You really think she put her own life at risk only so her reputation and career could be ruined while her abuser gets an outpouring of sympathy for having to deal with the "crazy lady" that he abused for years?

You might not be American, but you're engaging in the kind of backwards-thinking misogyny that Americans seem to love.
- Well, Amber Heard gained nothing and in fact seems poised to lose everything. Not to mention all the outrage against her.

It's not reasonable to think she's doing this for personal gain, considering she's gained nothing.

You're the one saying her thought process is "I know what I'll do! I'll throw away my reputation, my career and put my very life at risk all to generate an outpouring of support for someone I allegedly hate so much that I was willing to risk my own safety just to mildly inconvenience him!" Does that honestly seem like a reasonable thing to do to you? Do you honestly think that's how women think?
- True diversity cannot exist when people are allowed to commit or advocate for violence against groups they don't like. 

"Believing whatever they want to believe" is all well and good, until somebody believes that women are property and should be subdued with violence, or that transwomen aren't really women and deserve to be subjected to violence and erasure, or that other cultures exist for no other reason but as cheap window dressing for your stories about magical white people.

Diversity can only happen when everyone's accepting of everyone else. There is no room for bigots in diversity.
- We have all the evidence. You're refusing to see it because you want to support Amber Heard's abuser. 

Also? There's no such thing as "misandry." It's something made up by misogynists to discredit feminists. Sexism, like racism, requires institutional power and privilege. Men have the institutional power. Women aren't oppressing men, they literally can't.
- You've been shown the evidence. Repeatedly, now. 

She never admitted to abusing him, she admitted to hitting him. That's something women do in self defence, not abuse. 

Reverse racism isn't real. Racism involves institutional power and privilege. Just like sexism. Reverse sexism, your so-called "misandry," isn't real, either. It's something used by bigots to discredit those who oppose their bigotry.

You are flat-out wrong about misogyny. [Please, educate yourself](https://www.bustle.com/articles/71400-6-reasons-men-can-literally-never-be-victims-of-sexism-and-those-who-think-they)
- Misogyny, racism, homophobia, etc, literally *are* violence.

"Free speech" is little more than the rallying cry of the bigot with nothing left to defend their bigotry after being called out on it.

And, once again, considering so many white people can't seem to grasp this, [Reverse racism isn't real](https://www.vice.com/en_us/article/kwzjvz/dear-white-people-please-stop-pretending-reverse-racism-is-real). It's a racist attempt to redefine racism into something else that the oppressor class can wield against the oppressed.
- "Misandry?" 

We've already covered that [reverse sexism isn't real](https://www.bustle.com/articles/71400-6-reasons-men-can-literally-never-be-victims-of-sexism-and-those-who-think-they). It's just a cheap trick for sexists to try and weasel out of being called sexist.
- Honestly, considering the outpouring of support he's receiving, he wasn't even mildly inconvenienced.

People are rallying behind him because he's being "unfairly targeted" *by the woman he abused.* Nobody seems to care that he literally abused a woman. They're *praising* him for it, calling *him* the victim because she fought back against his abuse of her.

You're sick if you don't see the problem with that.
- And this right here? This is the kind of thinking that allowed the Nazis to rise to power.
- > White racism is a hundred times more common than black racism, but the New Black Panther Party still exists!

You say that as if the Black Panthers don't exist *because* of white racism. They are an *answer* to white racism, an attempt to fight back against the oppressors. 

It's not racist to fight back against your oppressors. That is why, again, [reverse racism doesn't exist](https://www.vice.com/en_us/article/kwzjvz/dear-white-people-please-stop-pretending-reverse-racism-is-real)

You can ignore the evidence that's been presented repeatedly, but that doesn't make it go away.
- The Nazis rose to power because nobody stopped them, preferring to "live and let live" with a group of murderous racists and not seeing how that could ever go wrong.

Attitudes like yours are what enable them to rise to power.
- But there isn't proof she abused him. All the proof says he abused her.

You need to educate yourself on domestic violence. Look up the Duluth model. It explains how domestic violence is the tool of the patriarchy that keeps women oppressed, establishes power and control over women, how women cannot benefit from male privilege or patriarchy, and how domestic violence reinforces male privilege and patriarchy, being a symptom of the misogyny that underlies the culture.
- And if you would just do the research, you'd learn that women don't do these things unless it's in self defence. The Duluth model explains this, that domestic violence is a tool of the patriarchy to reinforce male privilege against women. Women would gain literally nothing from committing violence against men in a patriarchy. Thus, when women are violent, it's proof that they are acting in self defence. 

You keep providing proof that Depp abused Amber Heard and calling it proof that Amber Heard, the VICTIM, abused her abuser.

Duluth makes this abundantly clear. You want to ignore that. That's misogyny.
- I've already shown you how this is wrong, and how this belief is racist and violent. Please stop. Read the evidence you have been provided. Educate yourself.
- > The fact that you can’t even differentiate between misandry and sexism 

You're the one saying that misandry, or "sexism against men," is a real thing. 

I can differentiate between "misandry" and "sexism just fine: Sexism is the systemic oppression of women by men, "misandry" is something made up by men as a way to insist that women rising up against their oppressors is equally bad as oppressing women, and isn't real. It's a lie that only serves to continue the oppression of women. It's misogyny.
- You've seen the evidence, over and over again. You've refused to acknowledge it, repeatedly. You're not arguing in good faith, you're simply engaging in misogyny. You have shown no interest in educating yourself, and I really doubt you have any ability to self-crit, either. You need to educate yourself on this issue. Resources have been provided. Make use of them. Seek more. Self-crit. Come back when you have a more educated view on the subject.
- There are no "male victims of domestic violence."

Seriously, read up on the Duluth model. It outlines it clearly. Domestic violence is the tool men use to reinforce their male privilege over women in a patriarchy. It is *literally impossible* for a woman to reinforce her male privilege over a man under patriarchy, because she has no male privilege. Women, therefore, can only use violence defensively, against their oppressors and abusers. If Amber Heard was violent against her abuser, then it was clearly in self defense.

Educate yourself.
- It's been provided. Repeatedly. You are the one failing to acknowledge it.

If one side provides evidence of a claim, and the other side closes their eyes, sticks their fingers in their ears and chants "lalala I can't see you I can't hear you you've proven nothing lalala," that doesn't make the evidence provided go away, it only reveals the other party's unwillingness to argue in good faith.

Come back when you have educated yourself on the subject with the many resources already supplied to you.
- Domestic violence is the process by which male privilege and patriarchy are enforced over women. 

I'm saying that under patriarchy, women cannot assert male privilege over a man. That's just logic.

The Duluth model would explain all of this to you if you cared to listen, instead of making sarcastic, misogynistic quips about it.
- She didn't though: Your own source is about how the alleged victim came forward to say Amber Heard was wrongfully accused, and how she was being slandered in order to make her abuser seem like the victim.

Congratulations, your own evidence proves you wrong.
- I've provided multiple links to videos, articles and news sources. You have ignored them all, insisting that I haven't provided any sources when clearly I have repeatedly.

I'm not the one trolling, here. Trolling would be to disingenuously insist that someone who has provided multiple sources has provided none.
- Lesbian relationships don't suffer from the same patriarchal power discrepancy as male/woman ones do. There is no domestic violence in those relationships because neither partner can reinforce their male privilege over the other, since both of them lack male privilege. 

It's not difficult to understand. I've answered every question you've asked. I can't help it if you don't like the answers, but you disliking the answer doesn't mean that no answer was provided.
- She didn't. She withdrew consent. That didn't stop the sexual encounter. That was rape.

Interestingly enough, the accused has a history of rape, and even one accusation of unwanted sexual contact against a man.

In short, you are defending a multiple rapist all so you can slander one of his victims.
- You're right: Men *aren't* violent for no reason, they're violent because of the advantages violence gives them through male privilege and patriarchy. Women do not gain similar benefits, because patriarchy and male privilege, by definition, are not things that benefit women.

Everything else you're saying is a lie. No serious scientific studies have ever even suggested such a thing, and the Duluth model is the most widely used program in the entire developed world. Are you seriously suggesting that the overwhelming majority of the developed world is wrong? Everyone except for you?
- It doesn't happen. Why would it? What would one partner have to gain by attempting to exercise male privilege over the other? How would that even work?

Violence is a symptom of male privilege. Male privilege comes from the patriarchy. Without male privilege, there can be no violence. Without patriarchy, there can be no male privilege. 

You seriously cannot be as obtuse as you are pretending to be, here.
- So it's gone from "you've provided no sources" to "you've provided a source, but I declare it invalid" to "ok, so well, that's two sources, but I hereby declare both invalid, and besides, there are no videos, so no evidence!"

Keep on moving the goalposts and revealing yourself to be a liar and a bad-faith troll, there. I've provided evidence repeatedly, including videos that you still refuse to acknowledge, even as you dismiss the evidence you've stopped pretending I didn't give.
- Depp got the advantage of establishing his male privilege over Amber Heard by abusing her. The benefit was partially to him (he kept her in fear, kept her doing what he wanted her to do, established his dominance and control over her) and partially to the patriarchy in general (by establishing that men can do these things to women, sending the message that no woman is ever safe in the presence of men).

[Educate yourself](https://www.youtube.com/watch?v=a4ST9Sd7WEE)

And you admit that the Duluth model is accepted by the experts nearly the whole world over, but you insist that you're smarter than all the experts combined? And the Duluth model is wrong because you say it is, regardless of what the experts say? Wow. I seriously hope you're trolling with that one.
- https://old.reddit.com/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgh275q/

Would you look at that? Me, linking a video.

https://old.reddit.com/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgeurcz/

Oh, look there! Me linking more videos!

No videos, huh? That's an awful lot of videos for no videos. Guess I didn't actually link those, then, though, did I?
- Her career wasn't kickstarted by this. She's been acting since 2004. Now, though, there are calls to end her career.

As for Depp, his career wasn't ruined by this. He's still out there, still working, still rich despite abusing his wife, and now with people rushing to offer him sympathy because the woman he beat and abused is trying to tell people about what he did.

Religion has nothing to do with anything. We're talking about how experta all over the world agree with the Duluth model, and the opposition consists of a bunch of nobody know-nothings on the internet. You really think you're smarter than every expert on the planet? Because that's what you're saying, that they're all wrong and only you are right, and if you believe that, then you need to seek therapy.
- Wikipedia? That thing that anyone can edit? I could make that article say "the number one leading cause of lesbian domestic violence is kittens batting yarn on Mars." Would that then be true?
- So, wait. . . You're contending that Ms. Van Ree, who you earlier claimed was a victim of Amber Heard, is now in league with her to smear Depp? That the whole thing is a massive lesbian conspiracy just to "get" one dude?

Are you seriously hearing yourself? That's delusional.
- You just said that the ex that Amber Heard allegedly abused is now on her side, part of the vast lesbian conspiracy to take down one mediocre white man. Make up your mind: Is Ms. Van Ree a victim of Amber Heard, or her partner in crime?
- The Duluth model holds that domestic violence is the process by which men assert their male privilege over women under patriarchy.

This precludes Amber Heard from being guilty of domestic violence because she cannot assert male privilege under patriarchy. The video you are refusing to watch talks extensively about the subject: Men are violent to assert dominance, women are violent to escape male violence. When a woman is violent against a man, it's out of self defense. If she admits to using violence against him, then, than that's proof that he was violent first.
- So she's walking back her claim that Amber Heard "abused" her? Then, by your own standards, doesn't that prove that she didn't abuse her?
- If she's not asserting her male privilege, then it's not domestic violence.

It doesn't matter if a man is differently-abled, they still have male privilege, and male privilege is *literally violence* against women. The violence that other men inflict on other women sends the message to every woman that "that could be me," and under patriarchy, all women are in fear for their lives at the hands of men. Whether they exercise their male privilege by way of violence is immaterial, the fact remains that they *could,* at any time, do so, and patriarchy makes this acceptable.

Educate yourself. This is basic stuff, right here. Your use of ableist slurs and language, though, and your refusal to self-crit and empathize with victims makes me seriously wonder if you're a troll, or if you're even *capable* of being anything other than a toxic male.
- I'm not the one denying science, facts, logic and reason.

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
66415	t3_f1gjcu	/r/fakehistoryporn/comments/f1gjcu/amber_heard...	Amber Heard, preparing to frame Johnny Depp, 2017	NaN	r/fakehistoryporn	2020-02-09 22:42:34	Neutral	Neutral	36851.0	NaN	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
66416	t1_fh6hsa8	/r/fakehistoryporn/comments/f1gjcu/amber_heard...	She cut off his finger, shit in his bed, and w...	t1_fh6gtos	r/fakehistoryporn	2020-02-10 01:45:16	Negative	Negative	742.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
66417	t1_fh6s1s7	/r/fakehistoryporn/comments/f1gjcu/amber_heard...	Explain	t1_fh6qdmw	r/fakehistoryporn	2020-02-10 03:18:24	Neutral	Neutral	8.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
66418	t1_fh6tb6r	/r/fakehistoryporn/comments/f1gjcu/amber_heard...	That's pathetic	t1_fh6pk4d	r/fakehistoryporn	2020-02-10 03:32:41	Negative	Negative	103.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
66419	t1_fh6wq1t	/r/fakehistoryporn/comments/f1gjcu/amber_heard...	Username checks out. No. No we can't.	t1_fh6vq0j	r/fakehistoryporn	2020-02-10 04:14:19	Neutral	Negative	31.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
84060	t1_fqdu0ze	/r/NudeCelebsOnly/comments/g617yi/amber_heard/...	Whatever I'd still hit it. You losers are just...	t3_g617yi	r/NudeCelebsOnly	2020-05-12 15:16:24	Negative	Negative	1.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84061	t1_fzzjmh7	/r/celebnsfw/comments/i1h20s/amber_heard/fzzjmh7/	Wow look at you trying to be edgy	t1_fzxips5	r/celebnsfw	2020-08-01 14:38:31	Negative	Positive	-12.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84062	t1_fzzkfdq	/r/celebnsfw/comments/i1h20s/amber_heard/fzzkfdq/	So? He sounds like a douchebag anyway	t1_fzxmeqb	r/celebnsfw	2020-08-01 14:45:45	Neutral	Neutral	-10.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84063	t1_g0098pf	/r/kotakuinaction2/comments/f7uuk5/amber_heard...	He probably had it coming	t3_f7uuk5	r/kotakuinaction2	2020-08-01 18:10:04	Neutral	Neutral	1.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84064	t1_g077l9m	/r/celebnsfw/comments/i1h20s/amber_heard/g077l9m/	You'll be eating my fist soon.	t1_g06c3ez	r/celebnsfw	2020-08-03 12:13:28	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84065	t1_g0crf0a	/r/celebnsfw/comments/i3nf2y/amber_heard_ass_i...	I'd still bang her. Don't care what the crying...	t3_i3nf2y	r/celebnsfw	2020-08-04 18:06:55	Negative	Negative	-20.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84066	t1_g0dcr6e	/r/celebnsfw/comments/i3nf2y/amber_heard_ass_i...	Thanks	t1_g0dcolv	r/celebnsfw	2020-08-04 20:20:12	Positive	Positive	-5.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84067	t1_g186d2d	/r/celebnsfw/comments/i8fz8u/amber_heard/g186d2d/	Who cares? Depp obviously deserves it	t1_g182s3j	r/celebnsfw	2020-08-12 16:15:49	Neutral	Positive	-216.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84068	t1_g187vgj	/r/celebnsfw/comments/i8fz8u/amber_heard/g187vgj/	I don't care what she's done. I'd marry her	t3_i8fz8u	r/celebnsfw	2020-08-12 16:26:34	Neutral	Negative	-68.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84069	t1_g18ao6g	/r/celebnsfw/comments/i8fz8u/amber_heard/g18ao6g/	Let me guess, did someone on 4chan tell you that?	t1_g18a20d	r/celebnsfw	2020-08-12 16:46:51	Neutral	Neutral	-7.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84070	t1_g18f0st	/r/celebnsfw/comments/i8fz8u/amber_heard/g18f0st/	Crybaby	t1_g18e7gl	r/celebnsfw	2020-08-12 17:18:46	Neutral	Neutral	-156.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84071	t1_g18ggrs	/r/celebnsfw/comments/i8fz8u/amber_heard/g18ggrs/	Nobody cares.	t1_g18ewy0	r/celebnsfw	2020-08-12 17:29:07	Neutral	Positive	-5.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84072	t1_g18hvhf	/r/celebnsfw/comments/i8fz8u/amber_heard/g18hvhf/	So she triggers a bunch of basement dwellers. ...	t1_g18giai	r/celebnsfw	2020-08-12 17:39:07	Negative	Neutral	-3.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84073	t1_g18jrsz	/r/celebnsfw/comments/i8fz8u/amber_heard/g18jrsz/	You poor fragile man	t1_g18j4h5	r/celebnsfw	2020-08-12 17:52:26	Negative	Negative	-85.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84074	t1_g18lhxf	/r/celebnsfw/comments/i8fz8u/amber_heard/g18lhxf/	Fragile male alert	t1_g18l32s	r/celebnsfw	2020-08-12 18:04:58	Neutral	Positive	-62.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84075	t1_g18mvei	/r/celebnsfw/comments/i8fz8u/amber_heard/g18mvei/	What an assumption.	t1_g18l93q	r/celebnsfw	2020-08-12 18:14:56	Neutral	Neutral	-1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84076	t1_g1913im	/r/celebnsfw/comments/i8fz8u/amber_heard/g1913im/	Lick my shitter like an apple fritter	t1_g18y242	r/celebnsfw	2020-08-12 20:01:24	Neutral	Positive	-10.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84077	t1_g192gjf	/r/celebnsfw/comments/i8fz8u/amber_heard/g192gjf/	Sesame street. Bring your pokemon cards you twat	t1_g1922th	r/celebnsfw	2020-08-12 20:12:03	Neutral	Negative	-1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84078	t1_g199869	/r/celebnsfw/comments/i8fz8u/amber_heard/g199869/	Lame	t1_g193szh	r/celebnsfw	2020-08-12 21:03:40	Negative	Negative	0.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84079	t1_g19ai73	/r/celebnsfw/comments/i8fz8u/amber_heard/g19ai73/	Guess I'll have to end you with my fists	t1_g199869	r/celebnsfw	2020-08-12 21:13:41	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84080	t1_g19eih8	/r/celebnsfw/comments/i8fz8u/amber_heard/g19eih8/	Nice job missing the insult you cunt. Don't be...	t1_g19apn5	r/celebnsfw	2020-08-12 21:45:48	Negative	Neutral	-2.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84081	t1_g19hei6	/r/celebnsfw/comments/i8fz8u/amber_heard/g19hei6/	Why are you gay?	t1_g19f75y	r/celebnsfw	2020-08-12 22:09:12	Positive	Neutral	-2.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84082	t1_g19jm33	/r/OnOffCelebs/comments/i838ip/amber_heard/g19...	Don't make me flex on you	t1_g19hn1x	r/OnOffCelebs	2020-08-12 22:27:11	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84083	t1_g19kunt	/r/OnOffCelebs/comments/i838ip/amber_heard/g19...	These 24in pythons you slut	t1_g19jyxv	r/OnOffCelebs	2020-08-12 22:37:20	Neutral	Negative	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84084	t1_g1ushwy	/r/celebnsfw/comments/iaycce/amber_heard/g1ushwy/	Still hot as fuck, I don't care what she's don...	t3_iaycce	r/celebnsfw	2020-08-17 13:34:58	Negative	Negative	-2.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84085	t1_g21b4w0	/r/celebnsfw/comments/i1h20s/amber_heard/g21b4w0/	Say that to my face hoe.	t1_g219egd	r/celebnsfw	2020-08-18 21:50:07	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84086	t1_g21ev7w	/r/celebnsfw/comments/i1h20s/amber_heard/g21ev7w/	I'll send you to the shadow realm	t1_g21b7oh	r/celebnsfw	2020-08-18 22:21:06	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84087	t1_g3ryuod	/r/celebnsfw/comments/ilct73/amber_heard/g3ryuod/	She's still perfect to me	t3_ilct73	r/celebnsfw	2020-09-02 22:09:37	Positive	Positive	-4.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84088	t1_g3rzzbm	/r/celebnsfw/comments/ilcs0b/amber_heard/g3rzzbm/	Nobody cares	t1_g3r3plk	r/celebnsfw	2020-09-02 22:19:35	Neutral	Positive	-36.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84089	t1_g3v7jb1	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	Fuck the haters, I'd still marry her	t3_ilrjf8	r/celebnsfw	2020-09-03 16:32:22	Negative	Negative	-18.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84090	t1_g3w9uos	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	You probably hate her because you know you'll ...	t1_g3vwwa4	r/celebnsfw	2020-09-03 20:11:16	Negative	Negative	-25.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84091	t1_g3wl93z	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	Fight me you hoe	t1_g3wkw36	r/celebnsfw	2020-09-03 21:16:01	Neutral	Negative	-15.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84092	t1_g3wq14d	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	3 star chips...now let's duel!!!	t1_g3wo9t2	r/celebnsfw	2020-09-03 21:47:48	Neutral	Neutral	-6.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84093	t1_g3yoxjx	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	Cry some more?	t1_g3y92us	r/celebnsfw	2020-09-04 09:27:53	Positive	Negative	-4.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84094	t1_g40blli	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	I'm gonna send you to the shadow realm	t1_g40biye	r/celebnsfw	2020-09-04 17:02:09	Neutral	Neutral	-1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84095	t1_g43w5qq	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	Fight me	t1_g43scvr	r/celebnsfw	2020-09-05 10:42:20	Neutral	Negative	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
84096	t1_g4bk70i	/r/celebnsfw/comments/ilrjf8/amber_heard_tits/...	Cause I'm gonna send you to the shadow realm	t1_g4awfg4	r/celebnsfw	2020-09-07 11:15:02	Neutral	Neutral	1.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
38125	t1_fgimk1c	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Ok how many times are we gonna keep seeing the...	t3_eyp2d3	r/videos	2020-02-04 14:17:27	Negative	Neutral	-19.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
38126	t1_fgsg0ly	/r/MensRights/comments/f098f7/petition_to_remo...	And only half of them are the PR firm hired by...	t3_f098f7	r/MensRights	2020-02-07 13:48:34	Negative	Negative	-48.0	submission	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
38127	t1_fgsgbi6	/r/MensRights/comments/f098f7/petition_to_remo...	No, because this story is all over the fucking...	t1_fgsfqct	r/MensRights	2020-02-07 13:52:28	Negative	Neutral	-197.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
38128	t1_fgshbx2	/r/MensRights/comments/f098f7/petition_to_remo...	You must not have been on this sub in the past...	t1_fgsgmjn	r/MensRights	2020-02-07 14:05:30	Positive	Positive	-118.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
38129	t1_fgshuia	/r/MensRights/comments/f098f7/petition_to_remo...	/r/imsmarterthanthisguy	t1_fgshpgs	r/MensRights	2020-02-07 14:11:56	Neutral	Neutral	-74.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN
38130	t1_fgsj2iz	/r/MensRights/comments/f098f7/petition_to_remo...	You're a pawn who's ruining discourse on this ...	t1_fgsiu14	r/MensRights	2020-02-07 14:26:46	Neutral	Negative	-24.0	comment	...	True	True	True	NaN	NaN	NaT	banned	banned	NaN	NaN

	user_name	subreddit	created_at
17416	knightfall1993	r/celebnsfw	2020-01-01 22:14:03
17417	knightfall1993	r/celebnsfw	2020-01-25 15:39:48
19132	kingsting1	r/Celebs	2020-01-03 22:57:34
19133	kingsting1	r/Celebhub	2020-07-15 02:18:17
19136	erica_hasten	r/celebnsfw	2020-01-04 01:29:59
...	...	...	...
101848	JudgeJayDredd	r/CelebritiesBunsButt	2020-10-26 16:51:26
101849	JudgeJayDredd	r/Celebnipplehub	2020-12-02 17:32:37
119785	jarek212	r/Celebhub	2020-11-25 12:46:25
126836	Embarrassed-Turn3573	r/celebnsfw	2020-12-17 15:09:27
127014	adamwarlock2887	r/JerkOffToCelebs	2020-12-20 19:45:04

	subreddit	created_at
user_name
armpit-lover	20	20
JeepersJCreepers	4	4
Alhana69	3	3
JudgeJayDredd	3	3
Agomemnon93	2	2
imsrikant	2	2
kingsting1	2	2
knightfall1993	2	2
BURTMACLIN007	2	2
simonoates1	2	2
CantStopThe_Signal	2	2

	user_name	subreddit	created_at
120809	rodrigohernandez4477	r/antifeminists	2020-11-28 11:00:44
120810	rodrigohernandez4477	r/Egalitarianism	2020-11-28 11:01:56
120812	rodrigohernandez4477	r/Feministpassdenied	2020-11-28 11:03:54
120813	rodrigohernandez4477	r/MRActivism	2020-11-28 11:04:41
120814	rodrigohernandez4477	r/masculinismo	2020-11-28 11:05:45
120815	rodrigohernandez4477	r/LadyMRAs	2020-11-28 11:06:24
120816	rodrigohernandez4477	r/HimToo	2020-11-28 11:06:49
120817	rodrigohernandez4477	r/JordanPeterson	2020-11-28 11:07:38
120818	rodrigohernandez4477	r/ProMaleCollective	2020-11-28 11:08:38
120819	rodrigohernandez4477	r/PussyPass	2020-11-28 11:09:49
120820	rodrigohernandez4477	r/MensRightsMeta	2020-11-28 11:10:22
120821	rodrigohernandez4477	r/MenToo	2020-11-28 11:14:05
120847	rodrigohernandez4477	r/AntiPinkPill	2020-12-05 19:54:52
120848	rodrigohernandez4477	r/LeftistsForMen	2020-12-05 19:56:16
120849	rodrigohernandez4477	r/TrueUnpopularOpinion	2020-12-05 19:57:45
120850	rodrigohernandez4477	r/TalesofPrivilege	2020-12-05 19:58:17
120851	rodrigohernandez4477	r/padresconderecho	2020-12-05 20:01:03
120852	rodrigohernandez4477	r/PadresConDerechos	2020-12-05 20:01:45
120853	rodrigohernandez4477	r/activism	2020-12-05 20:04:01
120854	rodrigohernandez4477	r/Equality	2020-12-05 20:04:52
120855	rodrigohernandez4477	r/SocialJusticeWarriors	2020-12-05 20:05:35
120856	rodrigohernandez4477	r/Toxic_Femininity	2020-12-05 20:06:07
120857	rodrigohernandez4477	r/socialjustice	2020-12-05 20:06:37
120858	rodrigohernandez4477	r/AgainstMisandry	2020-12-05 20:08:27
120859	rodrigohernandez4477	r/AbuseInterrupted	2020-12-05 20:15:22

	created_at	n_contributions
26	2020-02-04	652
24	2020-02-02	598
30	2020-02-08	418
29	2020-02-07	350
27	2020-02-05	341
31	2020-02-09	338
292	2020-11-07	300
331	2020-12-16	294
28	2020-02-06	246
112	2020-05-04	235

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
109110	t1_gbiux2y	/r/memes/comments/jpwz5n/im_looking_at_you_amb...	Hey /u/GOLDEN_eagle_420, thanks for contributi...	t3_jpwz5n	r/memes	2020-11-08 00:36:48	Positive	Neutral	0.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	57 days 23:27:16	57.0
109111	t1_gbiv0ov	/r/memes/comments/jpwz5n/im_looking_at_you_amb...	Hey /u/GOLDEN_eagle_420, thanks for contributi...	t3_jpwz5n	r/memes	2020-11-08 00:37:23	Positive	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	57 days 23:27:51	57.0
109112	t1_gbjzv8b	/r/memes/comments/jq24ya/fuck_amber_heard_man/...	Hey /u/memoryheadundertale, thanks for contrib...	t3_jq24ya	r/memes	2020-11-08 04:34:05	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	58 days 03:24:33	58.0
109113	t1_gbozc3m	/r/memes/comments/jqpble/amber_heard_is_big_ba...	Hey /u/The-one-no-one-wants, thanks for contri...	t3_jqpble	r/memes	2020-11-09 05:36:41	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	59 days 04:27:09	59.0
109114	t1_gbsespc	/r/memes/comments/jrbar1/all_i_want_for_christ...	Hey /u/Gatty-man-ting, thanks for contributing...	t3_jrbar1	r/memes	2020-11-10 02:40:03	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	60 days 01:30:31	60.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
109194	t1_gco76pe	/r/memes/comments/jux1dz/fuck_amber_heard/gco7...	Hey /u/tim_tam1, thanks for contributing to /r...	t3_jux1dz	r/memes	2020-11-18 01:01:19	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	67 days 23:51:47	67.0
109195	t1_gco7741	/r/memes/comments/juv03y/i_hate_amber_heard_so...	Hey /u/StrawHat44, thanks for contributing to ...	t3_juv03y	r/memes	2020-11-18 01:01:25	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	67 days 23:51:53	67.0
109196	t1_gco77i8	/r/memes/comments/jumihw/amber_heard_bad/gco77i8/	Hey /u/TrillaSuduri, thanks for contributing t...	t3_jumihw	r/memes	2020-11-18 01:01:32	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	67 days 23:52:00	67.0
109197	t1_gco78ky	/r/memes/comments/juceps/amber_heard_would_be_...	Hey /u/jafr_1226, thanks for contributing to /...	t3_juceps	r/memes	2020-11-18 01:01:48	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	67 days 23:52:16	67.0
109198	t1_gfujmgl	/r/memes/comments/jplx42/all_my_homies_hate_am...	Hey /u/ImASadRock, thanks for contributing to ...	t3_jplx42	r/memes	2020-12-14 20:33:46	Negative	Neutral	1.0	submission	...	True	False	False	-100.0	1.0	2020-09-11 01:09:32	unverified	2020	94 days 19:24:14	94.0

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
39852	t1_fgir6vq	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Lmao u think he killed him self cuz she kissed...	t1_fgil2th	r/videos	2020-02-04 15:11:17	Neutral	Neutral	-19.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 21:58:42	837.0
39853	t1_fgirfv3	/r/videos/comments/eyp2d3/audio_of_amber_heard...	It does tie to his suicide/murder. Just take a...	t1_fgilbn1	r/videos	2020-02-04 15:14:02	Positive	Negative	-5.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:01:27	837.0
39854	t1_fgirk48	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Bro I’m sorry to say this but Bourdain was int...	t1_fginhxh	r/videos	2020-02-04 15:15:19	Negative	Negative	-4.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:02:44	837.0
39855	t1_fgirt8q	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Bourdains death has nothing to with paying off...	t1_fgioprb	r/videos	2020-02-04 15:18:04	Negative	Neutral	-2.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:05:29	837.0
39856	t1_fgiry67	/r/videos/comments/eyp2d3/audio_of_amber_heard...	That’s exactly what happened, Bourdain couldn’...	t1_fgim092	r/videos	2020-02-04 15:19:33	Positive	Neutral	-4.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:06:58	837.0
39857	t1_fgis20m	/r/videos/comments/eyp2d3/audio_of_amber_heard...	99% of people at the UN, positions of power, c...	t1_fginutj	r/videos	2020-02-04 15:20:44	Negative	Neutral	25.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:08:09	837.0
39858	t1_fgis8y5	/r/videos/comments/eyp2d3/audio_of_amber_heard...	I didn’t kick u, I pushed u with my foot	t1_fgijynx	r/videos	2020-02-04 15:22:49	Neutral	Neutral	5.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:10:14	837.0
39859	t1_fgishym	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Males r disposable	t1_fgio7h2	r/videos	2020-02-04 15:25:33	Neutral	Neutral	5.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:12:58	837.0
39860	t1_fgisp6d	/r/videos/comments/eyp2d3/audio_of_amber_heard...	It’s a perfect example how the #metoo movement...	t1_fgijou1	r/videos	2020-02-04 15:27:40	Positive	Neutral	-6.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:15:05	837.0
39861	t1_fgisr24	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Proof or gtfo	t1_fgijglh	r/videos	2020-02-04 15:28:14	Neutral	Neutral	3.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:15:39	837.0
39862	t1_fgit44m	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Does that woman take no responsibility for her...	t1_fgijc5t	r/videos	2020-02-04 15:32:02	Negative	Neutral	-8.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:19:27	837.0
39863	t1_fgitc98	/r/videos/comments/eyp2d3/audio_of_amber_heard...	You know why, Reddit is partly responsible for...	t1_fgiokhf	r/videos	2020-02-04 15:34:25	Positive	Neutral	53.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:21:50	837.0
39864	t1_fgitmkn	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Doesn’t matter how much bullshit you type, doe...	t1_fgisx0m	r/videos	2020-02-04 15:37:25	Positive	Negative	34.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:24:50	837.0
39865	t1_fgitugg	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Just the ones where they “suicide” themselves ...	t1_fgis8yd	r/videos	2020-02-04 15:39:40	Positive	Positive	1.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:27:05	837.0
39866	t1_fgity72	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Paranoid? He killed himself and his girlfriend...	t1_fgisbhu	r/videos	2020-02-04 15:40:46	Negative	Neutral	-2.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:28:11	837.0
39867	t1_fgiwssm	/r/videos/comments/eyp2d3/audio_of_amber_heard...	I’m saying it doesn’t belong in the same realm...	t1_fgiwnwx	r/videos	2020-02-04 16:10:07	Neutral	Positive	-6.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:57:32	837.0
39868	t1_fgiwwql	/r/videos/comments/eyp2d3/audio_of_amber_heard...	It’s not, but ur also ignoring his girlfriends...	t1_fgiuh44	r/videos	2020-02-04 16:11:11	Neutral	Neutral	0.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:58:36	837.0
39869	t1_fgiwzdh	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Read ur comment again because justifying it is...	t1_fgiu77j	r/videos	2020-02-04 16:11:53	Positive	Neutral	14.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 22:59:18	837.0
39870	t1_fgix2pw	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Imagine being alive when trump is president & ...	t1_fgiu3yl	r/videos	2020-02-04 16:12:42	Positive	Positive	-1.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 23:00:07	837.0
39871	t1_fgizjfv	/r/videos/comments/eyp2d3/audio_of_amber_heard...	You typed a lot cuz it takes a lot of bullshit...	t1_fgix6p0	r/videos	2020-02-04 16:35:23	Negative	Neutral	34.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 23:22:48	837.0
39872	t1_fgj0tmp	/r/videos/comments/eyp2d3/audio_of_amber_heard...	^ emotional abuse	t1_fgj0c4r	r/videos	2020-02-04 16:47:02	Neutral	Neutral	0.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	837 days 23:34:27	837.0
39873	t1_fgj466o	/r/videos/comments/eyp2d3/audio_of_amber_heard...	You shouldn’t make any assumption before apply...	t1_fgj3isz	r/videos	2020-02-04 17:17:26	Negative	Negative	23.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	838 days 00:04:51	838.0
39874	t1_fgj9fy1	/r/videos/comments/eyp2d3/audio_of_amber_heard...	So you provided evidence & logic reasoning to ...	t1_fgj4qqi	r/videos	2020-02-04 18:06:54	Neutral	Neutral	2.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	838 days 00:54:19	838.0
39875	t1_fgj9i07	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Assumptions based on reasoning, instead of a b...	t1_fgj998q	r/videos	2020-02-04 18:07:27	Neutral	Positive	13.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	838 days 00:54:52	838.0
39876	t1_fgjfam2	/r/videos/comments/eyp2d3/audio_of_amber_heard...	All victims r telling the truth. The issue is ...	t1_fgjax0i	r/videos	2020-02-04 19:00:26	Positive	Neutral	3.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	838 days 01:47:51	838.0
39877	t1_fgjn3aj	/r/videos/comments/eyp2d3/audio_of_amber_heard...	Agreed	t1_fgjhkoi	r/videos	2020-02-04 20:17:13	Neutral	Positive	0.0	comment	...	False	False	False	-100.0	1.0	2017-10-19 17:12:35	unverified	others	838 days 03:04:38	838.0

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
90379	t1_fwvfmut	/r/awfuleverything/comments/hkp7lo/and_he_lost...	You shouldn’t. He probably did stuff to her to...	t1_fwudn3m	r/awfuleverything	2020-07-04 04:04:32	Positive	Neutral	1.0	comment	...	True	False	False	-100.0	11.0	2012-03-21 03:14:08	unverified	others	3027 days 00:50:24	3027.0
90380	t1_fx1awvt	/r/awfuleverything/comments/hkp7lo/and_he_lost...	Agreed Johnny should be put in prison. Fuck th...	t3_hkp7lo	r/awfuleverything	2020-07-05 21:21:40	Negative	Neutral	0.0	submission	...	True	False	False	-100.0	11.0	2012-03-21 03:14:08	unverified	others	3028 days 18:07:32	3028.0

	user_name	user_created_at	submission_comment	created_at
20571	gangbang_crasher	2019-10-31 20:53:48	submission	2020-01-22 14:31:26
21256	n0nouvurr3661t	2018-05-10 00:10:26	submission	2020-01-26 04:58:29
21984	User183749191737493	2019-10-15 20:31:49	submission	2020-01-30 03:28:57
66827	Trumps_Hair_Stylist	2016-01-14 05:49:30	submission	2020-02-10 07:00:48
69740	fapstar_	2020-01-12 10:25:57	submission	2020-02-23 15:37:20
69805	Rude_Awareness	2020-01-18 05:37:55	submission	2020-02-24 17:55:17
70788	onionslover	2020-02-26 00:53:18	submission	2020-03-06 21:06:49
72509	Boiledboxers1	2020-03-19 13:59:38	submission	2020-03-28 06:59:31
72510	Boiledboxers1	2020-03-19 13:59:38	submission	2020-03-28 06:59:36
72511	Boiledboxers1	2020-03-19 13:59:38	submission	2020-03-28 06:59:39
72512	Boiledboxers1	2020-03-19 13:59:38	submission	2020-03-28 06:59:41
72513	Boiledboxers1	2020-03-19 13:59:38	submission	2020-03-28 06:59:42
80361	boldbelsnickel	2019-11-12 20:28:11	submission	2020-04-22 22:39:02
81118	ThrilloftheHunt1	2019-08-26 22:53:07	submission	2020-09-07 20:14:40
84401	lorory390	2019-05-20 20:59:03	submission	2020-05-18 08:12:14
84405	lorory390	2019-05-20 20:59:03	submission	2020-08-18 04:53:25
85195	Cartaxer	2020-04-24 06:47:25	submission	2020-05-22 01:37:10
85196	Cartaxer	2020-04-24 06:47:25	submission	2020-05-23 12:09:52
85282	Sonic_Strom2200	2019-10-01 08:32:49	comment	2020-09-19 10:14:30
86525	baronzemo168	2018-08-12 07:46:57	submission	2020-05-31 13:26:26
86532	baronzemo168	2018-08-12 07:46:57	submission	2020-05-31 14:56:38
86533	baronzemo168	2018-08-12 07:46:57	submission	2020-05-31 17:17:35
86541	baronzemo168	2018-08-12 07:46:57	submission	2020-06-29 15:46:37
86542	baronzemo168	2018-08-12 07:46:57	submission	2020-07-01 10:32:55
86932	rangerguy34	2019-09-28 10:43:32	submission	2020-06-14 10:54:11
86959	PrizeBathroom	2020-03-24 10:29:57	submission	2020-06-15 19:09:06
87074	Kthrowaway24	2017-07-16 06:54:59	submission	2020-06-17 08:13:48
94570	celebfap4444	2020-05-23 03:09:03	submission	2020-07-17 02:50:11
94571	celebfap4444	2020-05-23 03:09:03	submission	2020-07-19 10:39:19
97664	camh5866	2020-04-13 01:05:32	submission	2020-07-31 22:31:12
98625	5nn4r3sar74wcugv	2020-07-26 21:27:52	comment	2020-11-28 14:00:18
99459	teriyaki7404	2020-05-29 07:26:18	submission	2020-09-10 09:54:11
99461	teriyaki7404	2020-05-29 07:26:18	submission	2020-09-10 15:10:33
99959	for--the--boys	2020-04-21 12:35:21	submission	2020-09-10 16:35:34
101024	sharp1ez	2015-01-16 08:12:14	submission	2020-10-11 01:56:10
101084	boy80878	2020-03-25 22:35:50	submission	2020-10-13 07:12:47
102714	Breach01	2019-04-08 04:13:05	submission	2020-11-05 00:51:04
112139	akultra	2015-11-22 03:45:37	submission	2020-11-09 19:36:06
122677	Axe126003	2019-08-15 03:50:51	submission	2020-12-06 22:27:51

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	...	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
36756	t3_eynqbw	/r/PurplePillDebate/comments/eynqbw/cmv_the_am...	CMV: The Amber Heard audio is typical of how w...	NaN	r/PurplePillDebate	2020-02-04 09:46:10	Negative	Neutral	360.0	NaN	...	False	False	False	8084.0	494.0	2015-02-07 23:46:15	unverified	others	1822 days 09:59:55	1822.0
39520	t3_eyr8tn	/r/unpopularopinion/comments/eyr8tn/johnny_dep...	Johnny Depp is as bad as Amber Heard	NaN	r/unpopularopinion	2020-02-04 14:59:52	Negative	Negative	1.0	NaN	...	False	False	False	0.0	1.0	2020-02-02 22:08:27	unverified	2020	1 days 16:51:25	1.0
39637	t3_eyrahl	/r/u_vmalakumaran/comments/eyrahl/audio_of_amb...	Audio of Amber Heard admitting she was the one...	NaN	u/vmalakumaran	2020-02-04 15:03:07	Neutral	Negative	2.0	NaN	...	False	False	False	0.0	5.0	2019-12-09 12:40:04	unverified	2019	57 days 02:23:03	57.0
40110	t3_eyriqm	/r/worldnews/comments/eyriqm/the_metoo_movemen...	The MeToo movement era of accusations without ...	NaN	r/worldnews	2020-02-04 15:18:59	Negative	Neutral	1.0	NaN	...	False	False	False	16738.0	12163.0	2015-07-12 02:55:08	unverified	others	1668 days 12:23:51	1668.0
42945	t3_eytg4s	/r/brasil/comments/eytg4s/mais_uma_nova_página...	Mais uma nova página na confusa do Johnny Depp...	NaN	r/brasil	2020-02-04 17:22:40	Neutral	Neutral	14.0	NaN	...	False	False	False	3553.0	1894.0	2019-08-19 21:39:22	unverified	2019	168 days 19:43:18	168.0
46890	t3_eyzqgu	/r/u_microwavefolder/comments/eyzqgu/audio_of_...	Audio of Amber Heard admitting she was the one...	NaN	u/microwavefolder	2020-02-04 23:53:06	Neutral	Negative	3.0	NaN	...	False	False	False	22.0	13.0	2020-01-24 23:46:58	unverified	2020	11 days 00:06:08	11.0

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	submission_text	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
36944	t3_eyp2d3	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/	Audio of Amber Heard admitting she was the one who was abusive towards Johnny Depp.	NaN	r/videos	2020-02-04 12:04:19	Neutral	Negative	98525.0	NaN	submission	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 10:49:17	192.0
36945	t1_fgieqh0	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgieqh0/	This is during a couples counseling session and there's a full hour of audio, somewhere.	t1_fgiemw1	r/videos	2020-02-04 12:26:39	Positive	Neutral	56.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 11:11:37	192.0
36946	t1_fgih2ye	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgih2ye/	I mean he admitted to leaving when she hit him, so I don't think he's quite as guilty as it seemed at first. \n\nAlso, if you're the one getting mad, it probably means you're the problem. He's cooled out, she's raving.	t1_fgigpxr	r/videos	2020-02-04 13:03:45	Negative	Negative	25.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 11:48:43	192.0
36947	t1_fgih6ec	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgih6ec/	Here's the full hour of audio: https://youtu.be/aca0KWoHtqQ\n\nThey recorded their conversations as a form of couples therapy and it was legally released.	t3_eyp2d3	r/videos	2020-02-04 13:05:08	Positive	Positive	13676.0	submission	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 11:50:06	192.0
36948	t1_fgihw01	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgihw01/	Listen to the full audio. She's a narcissistic lunatic that screams at him because he leaves when she's screaming at him and throwing stuff at him.	t1_fgihppx	r/videos	2020-02-04 13:15:27	Positive	Negative	1045.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:00:25	192.0
36949	t1_fgii3hp	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgii3hp/	I'm a man who was sexually assaulted by a drunk female friend.\n\nThis kind of shit makes it much harder to believe victims.	t1_fgihz0j	r/videos	2020-02-04 13:18:28	Positive	Neutral	35.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:03:26	192.0
36950	t1_fgiic5w	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgiic5w/	And she had the audacity to speak at the Women's March.	t1_fgii9qy	r/videos	2020-02-04 13:21:59	Neutral	Neutral	9798.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:06:57	192.0
36951	t1_fgiir6p	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgiir6p/	I mean every couple fights, but if it's happening for no good reason, if it's happening more than once in a while, and if there's physical abuse in any form, I'd say bail before she can take half your stuff.	t1_fgiilwz	r/videos	2020-02-04 13:27:51	Negative	Neutral	152.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:12:49	192.0
36952	t1_fgiixbd	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgiixbd/	She recorded it. But they both consented to the recording.	t1_fgihipf	r/videos	2020-02-04 13:30:11	Neutral	Neutral	27.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:15:09	192.0
36953	t1_fgijam7	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgijam7/	In the full audio she never once says he was the aggressor. She's angry because when she throws stuff at him and screams at him, he leaves so he doesn't need to get aggressive.	t1_fgij4ku	r/videos	2020-02-04 13:35:10	Negative	Negative	25.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:20:08	192.0
36954	t1_fgijd6s	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgijd6s/	Well, far be it from me to judge your relationship, but physical abuse and screaming aren't the hallmarks of a relationship that's healthy.	t1_fgijawn	r/videos	2020-02-04 13:36:09	Positive	Neutral	81.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:21:07	192.0
36955	t1_fgijhra	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgijhra/	Flicking a zippo.	t1_fgijd0x	r/videos	2020-02-04 13:37:52	Neutral	Neutral	15.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:22:50	192.0
36956	t1_fgikoho	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgikoho/	It was. They recorded their conversations so they could listen to them later as a form of therapy.	t1_fgikb9b	r/videos	2020-02-04 13:53:40	Neutral	Neutral	212.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:38:38	192.0
36957	t1_fgil3c1	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgil3c1/	It is. It separates you from the fight so you can listen more objectively later when you both calm down.	t1_fgil0zz	r/videos	2020-02-04 13:59:02	Positive	Neutral	150.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:44:00	192.0
36958	t1_fgilhzq	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgilhzq/	No, but it was recommended by a counselor, from what I understand.	t1_fgilfj0	r/videos	2020-02-04 14:04:13	Neutral	Neutral	55.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 12:49:11	192.0
36959	t1_fgin4nm	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgin4nm/	I mean he probably knew a lot of people there.	t1_fgimev9	r/videos	2020-02-04 14:24:26	Negative	Neutral	613.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 13:09:24	192.0
36960	t1_fgisefw	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgisefw/	Could have been a HIPAA or NDA issue. She was the one who recorded this.	t1_fgisc85	r/videos	2020-02-04 15:24:28	Neutral	Neutral	8.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:09:26	192.0
36961	t1_fgiss9c	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgiss9c/	Grow up seeing your parents fight, you start to think that's what love looks like.	t1_fgism2c	r/videos	2020-02-04 15:28:35	Positive	Neutral	5.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:13:33	192.0
36962	t1_fgitmp6	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgitmp6/	There's a trigger warning in the video. The guy that's narrating explains that the content might set some people off.	t1_fgitjl0	r/videos	2020-02-04 15:37:27	Neutral	Negative	3.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:22:25	192.0
36963	t1_fgitv2z	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgitv2z/	To be fair that's kinda what he's always sounded like.	t1_fgitr1x	r/videos	2020-02-04 15:39:51	Positive	Positive	5.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:24:49	192.0
36964	t1_fgiuwqn	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgiuwqn/	The full hour tells you quite a bit.	t1_fgiuqrj	r/videos	2020-02-04 15:50:47	Positive	Neutral	2.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:35:45	192.0
36965	t1_fgivayd	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgivayd/	And there are a lot of other tapes.	t1_fgiv6hq	r/videos	2020-02-04 15:54:50	Negative	Neutral	2.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:39:48	192.0
36966	t1_fgivmu4	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgivmu4/	https://www.youtube.com/watch?v=TeRtMRhTkVc	t1_fgivibv	r/videos	2020-02-04 15:58:07	Neutral	Neutral	1.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 14:43:05	192.0
36967	t1_fgj4743	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgj4743/	This audio is from 2015.	t1_fgj0flm	r/videos	2020-02-04 17:17:40	Neutral	Neutral	1.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 16:02:38	192.0
36968	t1_fgj50br	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgj50br/	I believe she did, because it was her recording.	t1_fgj4y5p	r/videos	2020-02-04 17:24:56	Neutral	Neutral	1.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 16:09:54	192.0
36969	t1_fgj76fh	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgj76fh/	Yeah but seriously though I hope there's a hell and he gets buttfucked by demons forever.	t1_fgj6xj6	r/videos	2020-02-04 17:44:42	Negative	Neutral	6.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 16:29:40	192.0
36970	t1_fgj8dmb	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgj8dmb/	One of Johnny Depp's security guys.	t1_fgj7pi5	r/videos	2020-02-04 17:56:28	Neutral	Positive	2.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 16:41:26	192.0
36971	t1_fgjc1hg	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fgjc1hg/	Yea. I mean he smokes and he's not a young man, but yeah.	t1_fgjbujx	r/videos	2020-02-04 18:28:25	Negative	Positive	2.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	192 days 17:13:23	192.0
36972	t1_fl288e7	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fl288e7/	Part of their counseling was recording their fights and listening to them later to gain perspective.	t1_fl20z51	r/videos	2020-03-20 22:58:54	Neutral	Neutral	1.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	237 days 21:43:52	237.0
36973	t1_fl2d72b	/r/videos/comments/eyp2d3/audio_of_amber_heard_admitting_she_was_the_one/fl2d72b/	And even when you're Johnny Depp, it still pays to be choosy.	t1_fl2d55d	r/videos	2020-03-20 23:52:03	Neutral	Neutral	1.0	comment	comment	audio_of_amber_heard_admitting_she_was_the_one	KindlyOlPornographer	True	False	False	False	157950.0	92848.0	2019-07-27 01:15:02	others	2019	237 days 22:37:01	237.0

	child_id	permalink	text	parent_id	subreddit	created_at	sentiment_blob	sentiment_nltk	score	top_level	submission_comment	submission_text	user_name	has_verified_email	is_mod	is_gold	is_banned	comment_karma	link_karma	user_created_at	banned_unverified	creation_year	diff	days_after_creation
31752	t1_fgd9ups	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgd9ups/	Nobody's seriously going to praise Rowling right now for anything. She sided with a man accused of abusing a woman, she sided with a transphobe, she still has a problem with LGBTQ representation, PoC representation, cultural appropriation. . . The list goes on and on.	t1_fgd0ywv	r/harrypotter	2020-02-02 21:50:57	Positive	Neutral	-301.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	275 days 23:48:40	275.0
31753	t1_fgerxqs	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgerxqs/	Except that when women lie about abuse, they're saying it's not happening, rather than that it is happening, and they're doing it out of a desire to protect their abuser, even at the expense of their own lives.\n\nNo woman has ever lied about having been abused. Some lie about having not been abused, but never about having been abused.	t1_fgem6kk	r/harrypotter	2020-02-03 05:31:34	Positive	Neutral	0.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	276 days 07:29:17	276.0
31754	t1_fges1i1	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fges1i1/	Men aren't the victims of domestic violence, though. They're the perpetrators.	t1_fge5uca	r/harrypotter	2020-02-03 05:33:12	Neutral	Neutral	-2.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	276 days 07:30:55	276.0
31755	t1_fgesx4b	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgesx4b/	We have Heard's testimony, and that video of him getting drunk and being abusive toward her.\n\nMore importantly, though, where's the proof that he wasn't abusive? That's the more important question.	t1_fgekjxk	r/harrypotter	2020-02-03 05:47:29	Positive	Neutral	-5.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	276 days 07:45:12	276.0
31756	t1_fget686	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fget686/	She wasn't, though. She sided with an abuser against his victim. She didn't do the right thing, she engaged in victim blaming, much like this thread is doing now.	t1_fgde96n	r/harrypotter	2020-02-03 05:51:40	Positive	Neutral	-5.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	276 days 07:49:23	276.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
31814	t1_fghn108	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fghn108/	You just said that the ex that Amber Heard allegedly abused is now on her side, part of the vast lesbian conspiracy to take down one mediocre white man. Make up your mind: Is Ms. Van Ree a victim of Amber Heard, or her partner in crime?	t1_fghkllq	r/harrypotter	2020-02-04 03:56:25	Negative	Negative	1.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	277 days 05:54:08	277.0
31815	t1_fgkhn3n	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgkhn3n/	The Duluth model holds that domestic violence is the process by which men assert their male privilege over women under patriarchy.\n\nThis precludes Amber Heard from being guilty of domestic violence because she cannot assert male privilege under patriarchy. The video you are refusing to watch talks extensively about the subject: Men are violent to assert dominance, women are violent to escape male violence. When a woman is violent against a man, it's out of self defense. If she admits to using violence against him, then, than that's proof that he was violent first.	t1_fgjg6dy	r/harrypotter	2020-02-05 01:22:57	Negative	Neutral	-2.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	278 days 03:20:40	278.0
31816	t1_fgkhr66	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgkhr66/	So she's walking back her claim that Amber Heard "abused" her? Then, by your own standards, doesn't that prove that she didn't abuse her?	t1_fgi5bgn	r/harrypotter	2020-02-05 01:24:11	Positive	Positive	0.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	278 days 03:21:54	278.0
31817	t1_fgleors	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fgleors/	If she's not asserting her male privilege, then it's not domestic violence.\n\nIt doesn't matter if a man is differently-abled, they still have male privilege, and male privilege is literally violence against women. The violence that other men inflict on other women sends the message to every woman that "that could be me," and under patriarchy, all women are in fear for their lives at the hands of men. Whether they exercise their male privilege by way of violence is immaterial, the fact remains that they could, at any time, do so, and patriarchy makes this acceptable.\n\nEducate yourself. This is basic stuff, right here. Your use of ableist slurs and language, though, and your refusal to self-crit and empathize with victims makes me seriously wonder if you're a troll, or if you're even capable of being anything other than a toxic male.	t1_fgldai6	r/harrypotter	2020-02-05 09:11:12	Negative	Neutral	-2.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	278 days 11:08:55	278.0
31818	t1_fngmu2v	/r/harrypotter/comments/exu3ki/actress_amber_heard_admits_she_hit_former_husband/fngmu2v/	I'm not the one denying science, facts, logic and reason.	t1_fngjsxp	r/harrypotter	2020-04-15 07:57:31	Neutral	Positive	1.0	comment	comment	actress_amber_heard_admits_she_hit_former_husband	Fantastic_Bat	True	False	False	False	4556.0	39.0	2019-05-02 22:02:17	others	2019	348 days 09:55:14	348.0

Accounts Creation Year	n_contributions
2020	20.8% (3548)
2019	23.4% (3989)
2018	13% (2212)
others	42.8% (7299)

Accounts Creation Year	n_submissions
2020	34.1% (174)
2019	26.8% (137)
2018	12.1% (62)
others	27% (138)

Accounts Creation Year	n_contributions
2020	10.7% (13722)
2019	15.7% (20104)
2018	10.2% (13125)
banned	7.97% (10235)
others	55.5% (71222)

Accounts Creation Year	n_contributions
2020	12.6% (996)
2019	13.3% (1048)
2018	7.41% (584)
banned	14.9% (1175)
others	51.8% (4080)

Case Study: Reddit Social Network Analysis Against Influence Operation¶

Table of Contents¶

Introduction¶

Exploratory Data Analysis¶

Banned / Unverified¶

Contributions¶

Peak Day Contributions¶

Submissions¶

Peak Day Submissions¶

Banned Accounts¶

Banned-Accounts largest scores¶

Banned-Accounts minimum scores¶

Contributions of Banned accounts in 2020¶

Contributions¶

Comments¶

Submissions¶

Banned Accounts Contributions Peaks¶

Which dates had the highest contrbitions of banned users?¶

Unverified Accounts¶

Explore unverified accounts with the largest link karma¶

Explore unverified accounts with the largest comment karma¶

Explore unverified accounts with the minimum link karma¶

Explore unverified accounts with the minimum comment karma¶

Explore the largest scores¶

Explore the minimum scores¶

Contributions of Unverified accounts in 2020¶

Unverified accounts contributions in 2020¶

Contributions¶

Peak day contributions 04-02-2020¶

Comments¶

Submissions¶

The account creation year of the unverified accounts contributed in 2020¶

Contributions¶

Submissions¶

Which dates had the highest contrbitions of unverified accounts?¶

New Vs Others¶

Contributions¶

Submissions¶

New Accounts¶

Last 3 Years¶

Contributions¶

Comments¶

Submissions¶

Accounts created in 2018¶

Contributions¶

Comments¶

Submissions¶

Accounts created in 2019¶

Contributions¶

Comments¶

Submissions¶

Accounts created in 2020¶

Contributions¶

Comments¶

Submissions¶

2020 Contributions Scores¶

Explore the largest scores¶

Explore the minimum scores¶

Conclusions¶

Banned / Unverified Accounts¶

Abou 20% of 2020 submissions were made by banned (14.9% --> 1175) and unverified (6.48% -> 511) accounts.¶

Banned¶

Unverified¶

Unverified Accounts Contributions in 2020¶

Unverified Accounts Submissions in 2020¶

New Accounts(Acoounts were made at¶

88% of 2020 submissions were made by newly created accounts (2018:2020).¶

New Accounts Contributions in 2020¶

New Accounts Submissions in 2020¶